Towards Academic Integrity: Using Bloom’s Taxonomy and Technology to Deter Cheating in Online Courses

Agha, Kakul; Zhu, Xia and Chikwa, Gladson (2022). Towards Academic Integrity: Using Bloom’s Taxonomy and Technology to Deter Cheating in Online Courses. In: Hamdan, A; Hassanien, A. E.; Mescon, T and Alareeni, B. eds. Technologies, Artificial Intelligence and the Future of Learning Post-COVID-19. Studies in Computational Intelligence. Studies in Computational Intelligence (1019). Cham: Springer, pp. 447–466.

DOI: https://doi.org/10.1007/978-3-030-93921-2_25

Abstract

One of the biggest challenges being faced in the higher education sector is academic dishonesty. While this phenomenon has been in existence for a long time, it is understood that the transition to remote online teaching and assessment due to the Covid-19 pandemic has exacerbated the challenge in higher education institutions (HEIs) across the globe. This chapter focuses on the discussion of the concept of academic dishonesty and the importance of ensuring academic integrity in HEIs in general and highlights some approaches that can be judiciously deployed by academicians to uphold academic integrity. This includes the use of Bloom’s Taxonomy in designing assessments and the creative use of technology to mitigate and deter cheating in online courses. The chapter makes a valuable contribution by providing some practical ideas that academicians can apply to enhance academic integrity while maintaining inclusivity and equitable student outcomes.

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